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Provider adapter for OpenAI ChatGPT","maintainers":[{"name":"bandofai","email":"it@bandofai.com"}],"readme":"# @bandofai/unido-provider-openai\n\n**OpenAI ChatGPT adapter for Unido applications.**\n\n[![npm version](https://img.shields.io/npm/v/@bandofai/unido-provider-openai)](https://www.npmjs.com/package/@bandofai/unido-provider-openai)\n[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)\n\nEnables your Unido applications to run as custom tools in ChatGPT using OpenAI's Custom Tools (formerly GPT Actions).\n\n---\n\n## Installation\n\n```bash\npnpm add @bandofai/unido-core @bandofai/unido-provider-openai zod\n```\n\n---\n\n## Quick Start\n\n```typescript\nimport { createApp, textResponse } from '@bandofai/unido-core';\nimport { openAI } from '@bandofai/unido-provider-openai';\nimport { z } from 'zod';\n\nconst app = createApp({\n  name: 'my-app',\n  version: '1.0.0',\n  providers: {\n    openai: openAI({ port: 3000 })\n  }\n});\n\napp.tool('greet', {\n  description: 'Greet a user',\n  input: z.object({\n    name: z.string()\n  }),\n  handler: async ({ name }) => {\n    return textResponse(`Hello, ${name}!`);\n  }\n});\n\nawait app.listen();\n// Server running on http://localhost:3000\n```\n\n---\n\n## Configuration Options\n\n### `openAI(options)`\n\nCreates an OpenAI provider configuration.\n\n**Options:**\n\n```typescript\n{\n  port?: number;         // Server port (default: 3000)\n  host?: string;         // Server host (default: 'localhost')\n  cors?: boolean;        // Enable CORS (default: true)\n  corsOrigin?: string;   // CORS origin (default: '*')\n}\n```\n\n**Examples:**\n\n```typescript\n// Default configuration\nopenAI()\n\n// Custom port\nopenAI({ port: 8080 })\n\n// Production configuration\nopenAI({\n  port: 3000,\n  host: '0.0.0.0',\n  cors: true,\n  corsOrigin: 'https://chat.openai.com'\n})\n\n// Restricted CORS\nopenAI({\n  cors: true,\n  corsOrigin: 'https://yourdomain.com'\n})\n```\n\n---\n\n## How It Works\n\n### Architecture\n\n```\nChatGPT → HTTP Request → OpenAI Adapter → Unido Core → Your Tool Handler\n                                        ← Universal Response ←\n         ← Formatted Response ←\n```\n\nThe OpenAI provider:\n\n1. **Starts HTTP Server** on the configured port\n2. **Implements MCP** (Model Context Protocol) for ChatGPT\n3. **Converts Schemas** from Zod to JSON Schema\n4. **Handles Requests** via Server-Sent Events (SSE)\n5. **Formats Responses** for OpenAI's expected format\n\n---\n\n## Connecting to ChatGPT\n\n### 1. Start Your Server\n\n```bash\npnpm run dev\n```\n\nYour server should be accessible at `http://localhost:3000` (or your configured port).\n\n### 2. Add to ChatGPT\n\n1. Open [ChatGPT](https://chat.openai.com/)\n2. Click your profile → **Settings**\n3. Go to **Custom Tools** section\n4. Click **Add Server**\n5. Enter your server URL: `http://localhost:3000`\n6. Click **Connect**\n\n### 3. Test It\n\nAsk ChatGPT to use your tools:\n- \"Greet me with my name\"\n- \"Calculate 5 + 3\"\n- \"What's the weather in London?\"\n\n---\n\n## Features\n\n### Server-Sent Events (SSE)\n\nThe OpenAI adapter uses SSE for real-time communication:\n\n```typescript\n// Endpoint: http://localhost:3000/sse\n// ChatGPT connects to this endpoint\n```\n\n### Health Checks\n\nBuilt-in health check endpoint:\n\n```bash\ncurl http://localhost:3000/health\n# Returns: {\"status\":\"ok\"}\n```\n\n### MCP Protocol\n\nImplements Model Context Protocol v2025-06-18:\n- `tools/list` - List available tools\n- `tools/call` - Execute a tool\n\n---\n\n## Advanced Features\n\n### Component Responses\n\nReturn rich UI that ChatGPT can render:\n\n```typescript\nimport { componentResponse } from '@bandofai/unido-core';\n\napp.tool('show_data', {\n  description: 'Display data in a card',\n  input: z.object({\n    title: z.string(),\n    description: z.string()\n  }),\n  handler: async ({ title, description }) => {\n    return componentResponse(\n      'card',\n      { title, description },\n      `${title}: ${description}`  // Fallback text\n    );\n  }\n});\n```\n\nRegister the underlying widget once when bootstrapping your app so the adapter can bundle it and expose the `ui://` resource to ChatGPT:\n\n```typescript\nconst userCardPath = fileURLToPath(new URL('./components/UserCard.tsx', import.meta.url));\n\napp.component({\n  type: 'user-card',\n  title: 'User Card',\n  sourcePath: userCardPath,\n  metadata: {\n    openai: {\n      renderHints: {\n        widgetAccessible: true,\n      },\n    },\n  },\n});\n```\n\nOn startup the adapter bundles every registered component with `esbuild`, converts it into an inline `ui://widget/<type>.html` resource, and serves it through the MCP `resources/list` and `resources/read` handlers used by ChatGPT Apps.\n\n### OpenAI Metadata\n\nThe adapter automatically adds OpenAI-specific metadata to tools:\n\n```json\n{\n  \"_meta\": {\n    \"openai/outputTemplate\": \"ui://widget/card.html\",\n    \"openai/widgetAccessible\": true\n  }\n}\n```\n\n---\n\n## Production Deployment\n\n### Environment Variables\n\n```bash\n# .env\nPORT=3000\nHOST=0.0.0.0\nCORS_ORIGIN=https://chat.openai.com\n```\n\nLoad in your app:\n\n```typescript\nimport { openAI } from '@bandofai/unido-provider-openai';\n\nconst app = createApp({\n  providers: {\n    openai: openAI({\n      port: parseInt(process.env.PORT || '3000'),\n      host: process.env.HOST || 'localhost',\n      corsOrigin: process.env.CORS_ORIGIN\n    })\n  }\n});\n```\n\n### Docker\n\nCreate `Dockerfile`:\n\n```dockerfile\nFROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json pnpm-lock.yaml ./\nRUN npm install -g pnpm && pnpm install --frozen-lockfile\n\nCOPY . .\nRUN pnpm run build\n\nEXPOSE 3000\n\nCMD [\"node\", \"dist/index.js\"]\n```\n\nBuild and run:\n\n```bash\ndocker build -t my-unido-app .\ndocker run -p 3000:3000 my-unido-app\n```\n\n### Hosting Platforms\n\nThe OpenAI provider works on any platform that supports HTTP servers:\n\n#### Railway\n\n```bash\n# railway.toml\n[build]\nbuilder = \"NIXPACKS\"\n\n[deploy]\nstartCommand = \"pnpm start\"\n```\n\n#### Render\n\n```yaml\n# render.yaml\nservices:\n  - type: web\n    name: my-unido-app\n    env: node\n    buildCommand: pnpm install && pnpm run build\n    startCommand: pnpm start\n```\n\n#### Vercel\n\n```json\n{\n  \"builds\": [\n    {\n      \"src\": \"dist/index.js\",\n      \"use\": \"@vercel/node\"\n    }\n  ],\n  \"routes\": [\n    {\n      \"src\": \"/(.*)\",\n      \"dest\": \"dist/index.js\"\n    }\n  ]\n}\n```\n\n---\n\n## Troubleshooting\n\n### \"Cannot find module '@modelcontextprotocol/sdk'\"\n\nThe SDK is a dependency. Reinstall:\n\n```bash\npnpm install\n```\n\n### \"Port already in use\"\n\nCheck what's using the port:\n\n```bash\nlsof -i :3000\n```\n\nKill it or use a different port:\n\n```typescript\nopenAI({ port: 3001 })\n```\n\n### ChatGPT can't connect\n\n**Check server is running:**\n```bash\ncurl http://localhost:3000/health\n```\n\n**Common issues:**\n- Firewall blocking connections\n- Using `https://` instead of `http://` for local dev\n- Server not bound to correct network interface\n\n**For production:**\n- Ensure server is publicly accessible\n- Use proper DNS/SSL if required\n- Check CORS settings\n\n### \"Tool not found\" in ChatGPT\n\nMake sure:\n1. Server is running\n2. Tool is registered before `app.listen()`\n3. ChatGPT connection is active (check settings)\n\n### Schema validation errors\n\nEnsure your Zod schemas are valid:\n\n```typescript\n// ❌ Wrong\ninput: z.object({\n  age: z.string().number()  // Invalid chain\n})\n\n// ✅ Correct\ninput: z.object({\n  age: z.number()\n})\n```\n\n---\n\n## API Details\n\n### HTTP Endpoints\n\n| Endpoint | Method | Description |\n|----------|--------|-------------|\n| `/` | GET | Root endpoint, returns server info |\n| `/health` | GET | Health check (`{\"status\":\"ok\"}`) |\n| `/sse` | GET | Server-Sent Events endpoint for MCP |\n\n### MCP Methods\n\n| Method | Description |\n|--------|-------------|\n| `tools/list` | List all available tools |\n| `tools/call` | Execute a specific tool |\n\n### Response Format\n\nTools return responses in this format:\n\n```typescript\n{\n  content: [\n    { type: 'text', text: 'Your response text' }\n  ]\n}\n```\n\nWith components:\n\n```typescript\n{\n  content: [\n    { type: 'text', text: 'Fallback text' }\n  ],\n  component: {\n    type: 'weather-card',\n    props: { city: 'London', temp: 18 }\n  }\n}\n```\n\n---\n\n## Examples\n\n### Basic Calculator\n\n```typescript\napp.tool('calculate', {\n  description: 'Perform arithmetic',\n  input: z.object({\n    op: z.enum(['add', 'sub', 'mul', 'div']),\n    a: z.number(),\n    b: z.number()\n  }),\n  handler: async ({ op, a, b }) => {\n    const ops = {\n      add: a + b,\n      sub: a - b,\n      mul: a * b,\n      div: a / b\n    };\n    return textResponse(`Result: ${ops[op]}`);\n  }\n});\n```\n\n### Weather Tool with Component\n\n```typescript\napp.tool('weather', {\n  description: 'Get weather for a city',\n  input: z.object({\n    city: z.string()\n  }),\n  handler: async ({ city }) => {\n    const weather = await fetchWeather(city);\n    return componentResponse(\n      'weather-card',\n      {\n        city,\n        temperature: weather.temp,\n        condition: weather.condition,\n        humidity: weather.humidity\n      },\n      `${city}: ${weather.temp}°C, ${weather.condition}`\n    );\n  }\n});\n```\n\n### Multi-Step Tool\n\n```typescript\napp.tool('analyze_code', {\n  description: 'Analyze code quality',\n  input: z.object({\n    code: z.string(),\n    language: z.enum(['javascript', 'typescript', 'python'])\n  }),\n  handler: async ({ code, language }) => {\n    // Step 1: Parse\n    const ast = await parser.parse(code, language);\n\n    // Step 2: Analyze\n    const issues = await analyzer.check(ast);\n\n    // Step 3: Format results\n    return componentResponse(\n      'code-analysis',\n      {\n        language,\n        issueCount: issues.length,\n        issues: issues.map(i => ({\n          line: i.line,\n          severity: i.severity,\n          message: i.message\n        }))\n      },\n      `Found ${issues.length} issues in ${language} code`\n    );\n  }\n});\n```\n\n---\n\n## Development\n\n### Running Tests\n\n```bash\ncd packages/providers/openai\npnpm test\n```\n\n### Building\n\n```bash\npnpm run build\n```\n\n### Type Checking\n\n```bash\npnpm run type-check\n```\n\n---\n\n## Links\n\n- **[Main Documentation](../../../README.md)** - Full framework docs\n- **[Core Package](../../core/)** - Core API documentation\n- **[npm Package](https://www.npmjs.com/package/@bandofai/unido-provider-openai)** - View on npm\n- **[OpenAI Platform](https://platform.openai.com/)** - OpenAI docs\n- **[MCP Specification](https://modelcontextprotocol.io/)** - Protocol details\n\n---\n\n## License\n\nMIT License - see [LICENSE](../../../LICENSE) for details.\n","readmeFilename":"README.md"}